Grouped People Counting Using mm-wave FMCW MIMO Radar

The problem of radar-based counting of multiple individuals moving as a single group is addressed using an mm-wave multiple-input-multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar. This problem is challenging because the different individuals are closer to each other than the range/azimuth resolution, and their bulk...

Sparsity-based Human Activity Recognition with PointNet using a Portable FMCW Radar

Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best...

FMCW Radar-Based Hand Gesture Recognition using Spatiotemporal Deformable and Context-Aware Convolutional 5D Feature Representation

Recently, frequency-modulated continuous-wave (FMCW) radar-based hand gesture recognition (HGR) using deep learning has achieved favorable performance. However, many existing methods use extracted features separately, i.e., using one of the range, Doppler, azimuth, or elevation angle information, or a combination of any two, to train...

Feature Extraction of Moving Automotive Vehicles using Multi-Target Tracking on Polarimetric Doppler Radar Data

Nowadays, many practical radar applications require an automatic interpretation of the received data, including data processing algorithms and target classification. The exploitation of additional polarimetric information is a very promising concept to improve the performance of automotive target classification. In this thesis work, we aim to...

Robust Feature Extraction Algorithm for analysis of Radar Targets using Multi-Object Tracking on Range Velocity Space

In this thesis, we propose, a Robust data extraction algorithm capable of extracting reliable target features of multiple moving targets of different classes over all channels of an S-Band Doppler Polarimetric Radar PARSAX. The proposed algorithm is capable of generating a time series data by tracking, clusters of detections - representing...

Voxel-Based Extraction and Classification of 3-D Pole-Like Objects From Mobile LiDAR Point Cloud Data

The digital mapping of road environment is an important task for road infrastructure inventory and urban planning. Automatic extraction and classification of pole-like objects can remarkably reduce mapping cost and enhance work efficiency. Therefore, this paper proposes a voxel-based method that automatically extracts and classifies three...